Many business and production scenarios require accurate visual inspection and automatic assessment of objects. Current applications for performing visual inspection and assessment perform comparisons of current images taken in real-time with a set of old images to assess change in the object. However, the conditions under which the current images are acquired impact the ability to obtain an accurate comparison. Specifically, factors, such as image position, alignment, orientation, and background, can lead to inaccuracies.
Image comparison to detect object changes also may be impacted by the different materials of which an object is comprised. Different materials, such as glass, plastic, rubber, wood, etc., may be altered in different manners due to their different mechanical behavior. This leads to further inaccuracies in the image comparison. Accordingly, current applications fail to provide an accurate image change assessment analysis based on the comparison of a current real-time image and a set of older images.